Data-Driven Inventory Control and Integrated Employee Involvement for Special Buys in Brick-and-Mortar Retail

Speaker: Alex Tschan, Project Manager, ALDI SE & Co. KG Murr

ALDI SÜD Germany launched the ‘Data-Driven Special Buys’ project in response to pandemic-related supply chain disruptions, market shifts, and increasing competition. This initiative combines advanced analytics and operations research with employee engagement to optimize product lifecycles. Ensuring practical relevance and applicability in business, including the satisfaction of all stakeholders involved (stores, national buying, project management, German board), was a high priority.

Methods used include: (1) multi-period optimization models (MIPs) for product allocation optimization, considering product demand and stock-keeping costs; (2) machine learning classification methods for store product allocation (“SAM”); (3) a proprietary algorithm (“ANA”) for just-in-time reallocations between stores; (4) a multi-period dynamic programming model (“DAVE”) for nationwide inventory control; (5) a sophisticated version of DAVE (“DAVE SDP”); (6) multivariate regression analyses for budget allocations of small product quantities for stores; and (7) a smartphone application (“Market-Whispering”) to engage 50,000 employees in product selection.

The project faced coordination challenges and required a strategic shift from decentralized to centralized inventory control. Proprietary software for the special buys product range improved operational efficiency, impacting the daily operations of 40,000 employees, and led to annual savings of several million euros in Germany.